Senior ML Researcher (AI)

TL;DR

Senior ML Researcher (AI/Knowledge Graphs): Developing novel methods for LLM-based ontology construction and semantic alignment across heterogeneous software artifacts with an accent on contradiction detection and knowledge graph reasoning. Focus on building a living spec extracted from the whole system to ensure product and architectural knowledge remains aligned.

Location: Must be based in one of the following: Amsterdam, Belgrade, Berlin, Limassol, Madrid, Munich, Paphos, Prague, Warsaw, or Yerevan. Flexible work location (home or office).

Company

hirify.global is a developer tools company; Spectrum is a resident of its startup incubator focusing on the semantic layer for software organizations.

What you will do

• Develop methods for LLM-based ontology construction from code, documentation, and issue trackers.
• Implement contradiction detection and reasoning over resulting knowledge graphs.
• Create datasets, metrics, and benchmarks to drive measurable system improvements.
• Prototype and validate research ideas, collaborating with ML and software engineers for production.
• Shape the research agenda in collaboration with hirify.global Research and external academic advisors.
• Publish research findings at top venues and represent the project in the research community.

Requirements

• PhD (or equivalent research experience) in NLP, knowledge graphs, ontology learning, or information extraction.
• Strong publication record in NLP or knowledge graph construction.
• Experience applying LLMs to structured knowledge extraction tasks.
• Experience designing and running rigorous experiments, ablation studies, and statistical evaluations.
• Strong Python and PyTorch skills with the ability to implement ideas from scratch.
• English: Proficiency in written and verbal communication required.

Nice to have

• Experience with ontology engineering, semantic web technologies (OWL, RDF, SPARQL), or ontology alignment.
• Background in code analysis or software engineering research.
• Experience with knowledge graph embedding methods or graph neural networks.
• Early-stage startup experience (zero-to-one phase).

Culture & Benefits

• Competitive salary and full support for publishing ML research and attending conferences.
• Startup autonomy backed by corporate resources and a generous runway.
• Flexible work location with the option to work from home or the office.
• Medical insurance allowance and professional mental health services.
• Learning and development opportunities, including language classes.
• Extra time off and sports benefits (on-site gym or stipend).